2023
DOI: 10.3390/app13020809
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Determination of Natural Fundamental Period of Minarets by Using Artificial Neural Network and Assess the Impact of Different Materials on Their Seismic Vulnerability

Abstract: Minarets are slender and tall structures that are built from different types of materials. Modern materials are also starting to be used in such structures with the recent developments in material technology. The seismic vulnerability and dynamic behavior of minarets can vary, depending on the material characteristics. Within this study’s scope, thirteen different material types used in minarets in Türkiye were chosen as variables. A sample minaret model was chosen as an example with nine different heights to … Show more

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Cited by 16 publications
(5 citation statements)
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“…Artificial neural networks (ANN), which is one of the machine learning methods, and particle swarm optimization (PSO), which is used in solving multidimensional problems, are frequently used in many areas [27][28][29][30][31][32]. In structural and earthquake engineering applications, these techniques have a critical impact on areas such as simulation, modeling, optimization, regression, and classification [33,34]. Some studies have also been carried out to predict the structural properties of reinforced concrete buildings under seismic loads, such as earthquakes with ANN [35][36][37][38][39][40].…”
Section: Introductionmentioning
confidence: 99%
“…Artificial neural networks (ANN), which is one of the machine learning methods, and particle swarm optimization (PSO), which is used in solving multidimensional problems, are frequently used in many areas [27][28][29][30][31][32]. In structural and earthquake engineering applications, these techniques have a critical impact on areas such as simulation, modeling, optimization, regression, and classification [33,34]. Some studies have also been carried out to predict the structural properties of reinforced concrete buildings under seismic loads, such as earthquakes with ANN [35][36][37][38][39][40].…”
Section: Introductionmentioning
confidence: 99%
“…The investigation of the effects of earthquakes on engineering structures in earthquake-prone parts of the Earth is a unique tool for determining the effects of the next ground motion [2]. In this case, much research in this area [3][4][5][6][7][8][9][10][11][12][13][14][15] has investigated the damage assessment and sustainability of RC buildings by using fragility curves and proposed a new model to evaluate damages for structures. On the other hand, the seismic response of buildings is also an important topic for earthquake engineering.…”
Section: Introductionmentioning
confidence: 99%
“…Ghasemi and Stephens [20] presented a machine learning clustering approach to group buildings of the same type and choose key buildings to study how they respond to and are damaged by earthquakes in the area. Işık et al [21] used the ANN method to assess the impact of different materials on seismic vulnerability. Jena et al [22] implemented the Long Short-Term Memory model for Geospatial Information Systems to assess the earthquake vulnerability for the whole of India.…”
Section: Introductionmentioning
confidence: 99%